Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

Analyzing missingness patterns in real-world data using the SMDI toolkit: application to a linked EHR-claims pharmacoepidemiology study.

BACKGROUND: Missing data in confounding variables present a frequent challenge in generating evidence using real-world data, including electronic health records (EHR). Our objective was to apply a recently published toolkit for characterizing missing data patterns and based on the toolkit results about likely missingness mechanisms, illustrate the decision-making process for analyses in an empirical case example. METHODS: We utilized the Structural Missing Data Investigations (SMDI) toolkit to characterize missing data patterns in the context of a pharmacoepidemiology study comparing cardiovascular outcomes of initiating sodium-glucose-cotransporter-2 inhibitors (SGLT2i) and dipeptidyl peptidase-4 inhibitors (DPP-4i) among older adults. The study used a linked EHR-Medicare claims dataset from Duke Health patients (2015-2017), focusing on partially observed confounders from EHR data (HbA1c lab and body mass index [BMI] values). Our analysis incorporated SMDI's descriptive functions and diagnostic tests to explore missingness patterns and determine missingness mitigation approaches. We used findings from these investigations to inform estimation of adjusted hazard ratios comparing the two classes of medications. RESULTS: High levels of missingness were noted for important confounding variables including HbA1c (63.6%) and BMI (16.5%). Diagnostic tests resulted in output that described: 1) the distributions of patient characteristics, exposure, and outcome between patients with or without an observed value of the partially observed covariate, 2) the ability to predict missingness based on observed covariates, and 3) estimate if the missingness of a partially observed covariate is differential with respect to the outcome. There was evidence that missingness could be sufficiently described using observed data, which allowed multiple imputation by chained equations using random forests to address missing confounder data in estimating treatment effects. Multiple imputation resulted in improved alignment of effect estimates with previous studies. CONCLUSIONS: We were able to demonstrate the practical application of the SMDI toolkit in a real-world setting. Application of the SMDI toolkit and the resulting insights of potential missingness patterns can inform the choice of appropriate analytic methods and increase transparency of research methods in handling missing data. This type of approach can inform analytic decision making and may increase our ability to generate evidence from real-world data.

Use of Hydrochlorothiazide in the United States Following Label Update About Skin Cancer Risk.

PURPOSE: On August 20, 2020, the United States (U.S.) Food and Drug Administration (FDA) issued a Drug Safety Communication (DSC) along with labeling updates to inform the public about a small increased risk of non-melanoma skin cancer (NMSC) associated with hydrochlorothiazide (HCTZ) use. This study aims to assess whether the DSC impacted HCTZ use in the U.S. METHODS: We conducted a trend analysis in the Sentinel Distributed Database using national healthcare administrative data from January 2017 to November 2022. We identified two cohorts each month: An overall cohort of all enrollees and a skin cancer cohort of those with a history of NMSC. For each cohort, we plotted the monthly proportion of patients receiving HCTZ-containing products among those receiving any thiazide diuretics. We performed interrupted time series analyses to quantify the impact of the DSC on these monthly proportions. Secondary analyses were conducted on the proportion of HCTZ users among patients receiving any antihypertensives. RESULTS: In the overall cohort, the DSC was only associated with a statistically significant but clinically negligible trend change of monthly HCTZ proportion within this cohort (0.018%; 95% CI, 0.012%-0.025%). Similar results were observed in the skin cancer cohort. The secondary analysis found no significant level change or trend change in the monthly proportion of HCTZ use among antihypertensive users. CONCLUSIONS: We did not observe significant changes in HCTZ use following the DSC about its NMSC risk, among the overall population and those with a history of NMSC. Our findings were in accordance with the DSC recommendation.

The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).

PURPOSE: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making. METHODS: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives. RESULTS: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed. CONCLUSIONS: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.

Travel to Mexico and uropathogen-antibiotic susceptibility mismatch in the emergency department.

INTRODUCTION: International travel results in an increased risk of colonization and infection with multidrug-resistant organisms. This study aimed to determine if recent travel to Mexico affects the rate of uropathogen-antibiotic susceptibility mismatch (UASM) in outpatients treated for urinary tract infection (UTI) in a South Texas emergency department (ED). METHODS: A retrospective cohort of adult patients presenting to the ED and treated outpatient for UTI from October 1, 2014, to February 25, 2020, was conducted at a community hospital located within approximately 15 miles of the United States-Mexico border. Rates of UASM were compared between patients with a history of recent travel to Mexico and those who have not recently traveled. RESULTS: A total of 192 patients were included, with 64 in the travel to Mexico group and 128 in the no travel group. UASM was significantly higher in the recent travel to Mexico group when compared to the no travel group (RR 1.49, 95% CI 1.03-2.13). Antibiotics most commonly associated with UASM included fluoroquinolones, cephalexin, and sulfamethoxazole-trimethoprim. There was no significant difference between the rates of resistance to first-line agents for the treatment of UTI among the two groups. CONCLUSION: In addition to known antibiotic resistance risk factors, recent travel to Mexico may increase the risk of UASM for ED patients with UTI. Considering the potential consequences of UTI treatment failure, antimicrobial stewardship services in the ED should include screening for antibiotic resistance risk factors and urine culture follow-up to ensure appropriate outpatient antibiotic therapy, especially among patients with recent international travel.

Knowledge and beliefs, behaviors, and adherence among Latino parents or legal guardians related to antibiotic use for upper respiratory tract infections in children under 6 years of age.

OBJECTIVE: Evaluate parents or legal guardians' knowledge and beliefs, behaviors, and adherence regarding antibiotic use for upper respiratory tract infection (URTI) in their children who are younger than 6 years. DESIGN: A cross-sectional study from September 2016 to February 2017. SETTING: Emergency department with a pediatric unit. PARTICIPANTS: One hundred and one parents or legal guardians who visited one of the selected emergency departments during the study period. INTERVENTION: Administration of a validated questionnaire to assess knowledge and beliefs, behaviors, and adherence regarding antibiotic use for URTI. MAIN OUTCOME MEASURES: Knowledge and beliefs, behaviors, and adherence regarding antibiotic use for URTI. RESULTS: Items with the least desired scores were seen in the "knowledge and beliefs" domain. Higher number of antibiotics used for URTI during the last year (P < 0.01) and lower education level (P = 0.03) were associated with least desired knowledge and beliefs scores. The "behaviors" domain contained the items with the best scores: higher education level (P = 0.05), fewer antibiotics used for URTI during the last year (P = 0.05), and older age (P = 0.02) were the only variables associated with better behaviors. For the "adherence" domain, lower education level (P < 0.01) was associated with poor indicators of adherence. The Cronbach alpha for the "knowledge and beliefs" items was 0.875, the "behaviors" items 0.569, and the "adherence" items 0.798. CONCLUSION: Findings of our study support the need for proper antibiotic education among parents, especially in those with an increased risk of antibiotic misuse and overuse. Pharmacists and physicians need to establish a dialogue with parents or legal guardians to discuss how antibiotics work, what types of infection they treat, and how to prevent antibiotic resistance. Sociodemographic variables can be used to identify at-risk groups and to develop successful interventions.

Knowledge and Perceptions of E-cigarettes and the Motivations for their Use: Talking to Smokers (E-cigarettes and/or Conventional Cigarettes) and Non-smokers in Puerto Rico.

OBJECTIVE: The awareness and use of e-cigarettes have been increasing in recent years. The World Health Organization recently reported that regulations are needed to impede the promotion of e-cigarettes to young people, prohibit unproven health claims about them (including those regarding smoking-cessation efficacy), minimize potential health risks to e-cigarette users and non-users, and protect existing tobacco controls. The study described herein explored e-cigarette knowledge, perceptions, and usage motivations among a group of adults in Puerto Rico. METHODS: This research study used a validated questionnaire with closed-ended questions to gather data. Non-inferential and inferential statistics were used to characterize smokers (of e-cigarettes, of conventional cigarettes, and of both) and non-smokers. RESULTS: A total of 415 respondents took part; they were evenly distributed by gender, age, and socioeconomic status; all were residents of Puerto Rico at the time of the survey. The overall awareness of e-cigarettes was high, but knowledge of nicotine content and regulations was limited. Asked whether e-cigarettes contain nicotine (they do not), approximately two thirds stated either that they do or that they didn't know; asked whether e-cigarettes are regulated as a tobacco product (they are in Puerto Rico), 84% stated either that they are not or that they didn't know. Common perceptions of e-cigarettes are that they are harmful to health and that they are no less harmful than cigarettes are. However, a significant portion of the respondents perceived e-cigarettes to be less addictive than conventional cigarettes are. Overall, the respondents were divided on the efficacy of e-cigarettes for smoking cessation. Nonetheless, the most common motivation for their use, according to both current users and potential future users, is to aid in smoking cessation or reduction. CONCLUSION: The majority of individuals surveyed were aware of e-cigarettes but had limited knowledge of their contents or regulation. As an aid in smoking cessation was the most commonly mentioned motivation for e-cigarette use.

Prevalence of Concurrent Prescribing of ACE-Is and ARBs among Beneficiaries of Puerto Rico's Government-Sponsored Health Care Plan During 2012 and 2013.

OBJECTIVE: Cardiovascular conditions are the second cause of death in Puerto Rico. The individual use of angiotensin-converting enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs) is considered the first-line therapy for the treatment of several cardiovascular-related medical conditions. However, the concurrent use of these 2 therapeutic classes of drugs is not supported by treatment guidelines. Studies have shown that their concurrent use represents a potential health risk. The research described in this paper aimed to determine the prevalence of the concurrent prescription of ACE-Is and ARBs, either separately or as a combination product, in a group of beneficiaries of the Puerto Rico Health Services Administration (ASES, by its initials in Spanish). METHODS: A 2-year cross sectional study was conducted. All pharmacy claims from the years 2012 and 2013 were provided by ASES and subsequently evaluated by the investigators to identify those involving the prescription of an ACE-I, an ARB, or a combination of drugs belonging to both therapeutic classes. Each pharmacy claim was complemented with sociodemographic and clinical data. The final dataset was analyzed at the person-month level using frequency, cumulative frequency, percentage, and cumulative percentage. RESULTS: The final sample consisted of 361,841 beneficiaries. A total of 23,598 beneficiaries were excluded because of incomplete diagnostic information. Of the beneficiaries with complete information, 36,202 out of 338,243 (10.7%) had concurrent prescriptions for ACE-Is and ARBs during the study period. We excluded 1,124 beneficiaries who had a primary diagnosis of HF, resulting in a final pool of 35,078 beneficiaries (10.4%) who had prescriptions for combination products. CONCLUSION: An unacceptable pattern of ACE-I and ARB co-prescribing during the years 2012 and 2013 was observed in patients with diagnoses for which the combination is not clinically indicated.

Cost-Utility Study of Warfarin Genotyping in the VACHS Affiliated Anticoagulation Clinic of Puerto Rico.

OBJECTIVE: To evaluate the cost-utility of the pharmacogenetic-guided dosing of warfarin (PGx), when compared to the current dosing strategy. METHODS: A Markov model was developed to assess the impact of the genotypingguided warfarin dosing in a hypothetical cohort of patients. The model was based on the percentage of time patients spent within the therapeutic international normalized ratio (INR) range (PTTR). PTTR estimates and genotype distribution were derived from a cohort of patients (n = 206) treated in the Veteran Affairs Caribbean Healthcare System (VACHS) and from results of other research study. Costs, utilities and event probability data were obtained from the literature. Probabilistic and one-way sensitivity analyses were performed to explore the range of plausible results. Willingness to pay was established at $50,000 per Quality Adjusted Life Year (QALY) gained. RESULTS: According to our model, the PGx strategy showed a QALY increase of 0.0021, with an increase in total cost of $272. This corresponds to an incremental cost-utility ratio (ICUR) of $127,501, ranging from $95,690 to $148,611. One-way sensitivity analysis revealed that the ICURs were more sensitive to the cost of genotyping and the effect of genotyping on the PTTR. CONCLUSION: Our model suggests that the warfarin PGx was not superior to the standard of care dosing strategy in terms of cost-utility.

A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records.

Objective: Partially observed confounder data pose challenges to the statistical analysis of electronic health records (EHR) and systematic assessments of potentially underlying missingness mechanisms are lacking. We aimed to provide a principled approach to empirically characterize missing data processes and investigate performance of analytic methods. Methods: Three empirical sub-cohorts of diabetic SGLT2 or DPP4-inhibitor initiators with complete information on HbA1c, BMI and smoking as confounders of interest (COI) formed the basis of data simulation under a plasmode framework. A true null treatment effect, including the COI in the outcome generation model, and four missingness mechanisms for the COI were simulated: completely at random (MCAR), at random (MAR), and two not at random (MNAR) mechanisms, where missingness was dependent on an unmeasured confounder and on the value of the COI itself. We evaluated the ability of three groups of diagnostics to differentiate between mechanisms: 1)-differences in characteristics between patients with or without the observed COI (using averaged standardized mean differences [ASMD]), 2)-predictive ability of the missingness indicator based on observed covariates, and 3)-association of the missingness indicator with the outcome. We then compared analytic methods including "complete case", inverse probability weighting, single and multiple imputation in their ability to recover true treatment effects. Results: The diagnostics successfully identified characteristic patterns of simulated missingness mechanisms. For MAR, but not MCAR, the patient characteristics showed substantial differences (median ASMD 0.20 vs 0.05) and consequently, discrimination of the prediction models for missingness was also higher (0.59 vs 0.50). For MNAR, but not MAR or MCAR, missingness was significantly associated with the outcome even in models adjusting for other observed covariates. Comparing analytic methods, multiple imputation using a random forest algorithm resulted in the lowest root-mean-squared-error. Conclusion: Principled diagnostics provided reliable insights into missingness mechanisms. When assumptions allow, multiple imputation with nonparametric models could help reduce bias.

Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy.

While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.

smdi: an R package to perform structural missing data investigations on partially observed confounders in real-world evidence studies.

Objectives: Partially observed confounder data pose a major challenge in statistical analyses aimed to inform causal inference using electronic health records (EHRs). While analytic approaches such as imputation are available, assumptions on underlying missingness patterns and mechanisms must be verified. We aimed to develop a toolkit to streamline missing data diagnostics to guide choice of analytic approaches based on meeting necessary assumptions. Materials and methods: We developed the smdi (structural missing data investigations) R package based on results of a previous simulation study which considered structural assumptions of common missing data mechanisms in EHR. Results: smdi enables users to run principled missing data investigations on partially observed confounders and implement functions to visualize, describe, and infer potential missingness patterns and mechanisms based on observed data. Conclusions: The smdi R package is freely available on CRAN and can provide valuable insights into underlying missingness patterns and mechanisms and thereby help improve the robustness of real-world evidence studies.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States.

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability. Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE. Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US. Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Improving data capture of race and ethnicity for the Food and Drug Administration Sentinel database: a narrative review.

PURPOSE: The U.S. Food and Drug Administration's Sentinel System is a national medical product safety surveillance system consisting of a large multisite distributed database of administrative claims supplemented by electronic health-care record data. The program seeks to improve data capture of race and ethnicity for pharmacoepidemiology studies. METHODS: We conducted a narrative literature review of published research on data augmentation and imputation methods to improve race and ethnicity capture in U.S. health-care systems databases. We focused on methods with limited (five-digit ZIP codes only) or full patient identifiers available to link to external sources of self-reported data. We organized the literature by themes: (1) variation in data capture of self-reported data, (2) data augmentation from external sources of self-reported data, and (3) imputation methods, including Bayesian analysis and multiple regression. RESULTS: Researchers reduced data missingness with high validity for Asian, Black, White, and Pacific Islander racial groups and Hispanic ethnicity. Native American and multiracial groups were difficult to validate due to relatively small sample sizes. CONCLUSIONS: Limitations on accessible self-reported data for validation will dictate methods to improve race and ethnicity data capture. We recommend methods leveraging multiple sources that account for variations in geography, age, and sex.

Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.

INTRODUCTION: Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance. METHODS: To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices. RESULTS: We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations. CONCLUSION: Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance.

Perceived value of self-monitoring blood glucose by primary care physicians and endocrinologists.

The value of self-monitoring blood glucose (SMBG) in patients with non-insulin-treated type 2 diabetes (NITT2DM) has been debated; however, the practice remains common. Patient perception of SMBG has been documented in several qualitative studies. However, the literature is lacking on the perceived value of SMBG by providers. This study used a structured questionnaire to evaluate and compare the perceived value, recommended frequency, and utility of SMBG in patients with NITT2DM by primary care providers (PCPs) and endocrinologists. A total of 70 PCPs and 14 endocrinologists completed the questionnaire. The results suggest that PCPs and endocrinologists find the practice of SMBG valuable in NITT2DM and believe it promotes behavioral changes in their patients. However, endocrinologists tend to recommend more frequent SMBG and find SMBG values more useful in making medication decisions. Conversely, PCPs tend to find the hemoglobin A1c more valuable than SMBG in making medication adjustments.

TV Advertising, Corporate Power, and Latino Health Disparities.

INTRODUCTION: This study identifies mental health, tobacco prevention, alcohol/beer, food/beverage, pharmaceutical, and other health-related advertisements across Spanish- and English-language TV networks owned by the same parent media company in the U.S. as commercial determinants of health disparities for Latino populations and/or viewers of Spanish-language TV. METHODS: A 3-week composite sample of Telemundo and National Broadcasting Company prime-time TV owned by the same parent media company was randomly drawn from March 31, 2021 to June 12, 2021 in Houston, Texas. A total of 1,593 health-related advertisements were yielded for systematic content analysis. Analyses included intercoder reliability, descriptive and bivariate analysis, and rate ratio and rate difference calculations. RESULTS: Telemundo had significantly more health-adverse and fewer health-beneficial advertisements than National Broadcasting Company. Telemundo broadcasted about 11 more alcohol (95% CI=9.1, 12.5) and 5 more unhealthy/noncore food/beverages (95% CI=2.0, 7.2) advertisements per hour of TV advertisement programming than the National Broadcasting Company. Telemundo also broadcasted about 1 fewer mental health/tobacco prevention (95% CI= -0.9, -0.2), 3 fewer healthy/core food/beverages (95% CI= -1.5, -4.3), and 4 fewer pharmaceutical (95% CI= -2.4, -5.7) advertisements per hour of advertisement programming than the National Broadcasting Company. CONCLUSIONS: Overall greater health-adverse and fewer health-beneficial advertisements are broadcasted on Spanish-language than on English-language TV. Unchecked corporate marketing strategies may serve as a commercial determinant of health disparities for Latino populations by Spanish-language TV.

Early Real-World Data to Assess Benefits and Risks of COVID-19 Vaccines: A Systematic Review of Methods.

Since the authorization of the first COVID-19 vaccines in December 2020, multiple studies using real-world data (RWD) have been published to assess their effectiveness/safety profile. This systematic review aimed to characterize the methods and outcomes of studies using RWD for assessment of COVID-19 vaccines, four months after vaccine approval. MEDLINE and EMBASE were searched to identify published studies until 6 May 2021. Two independent researchers selected relevant publications and extracted data from included studies. The risk of bias was assessed using New-Castle Ottawa tools. After screening 1086 studies, 15 were included. Out of the 15 studies, 12 (80%) followed a cohort design, 8 (53%) were based on USA data, 7 (47%) assessed health care professionals, and 14 articles (93%) assessed the BNT162b2 vaccine. Data sources included institutional databases, electronic health records, and patient-generated data. The primary endpoint mainly described was SARS-CoV-2-infection. Hospitalization and mortality were assessed in 2 studies. For the comparability domain, six studies (40%) had a high risk of bias. A few months after the beginning of COVID-19 vaccination, Real-world Evidence (RWE) provided timely safety surveillance and comparative effectiveness with findings that showed similar findings to Randomized control trial (RCT). Most of the initiatives assessed BNT162b2 and were conducted in the USA and used healthcare workers' data.

Prevalence of statin utilization and adherence among privately insured subjects in the Commonwealth of Puerto Rico.

BACKGROUND: Puerto Ricans are the Hispanic subgroup with the highest adjusted prevalence of statin-eligible patients. However, no study has described statin utilization and adherence among subjects living on the island of Puerto Rico. OBJECTIVES: To (a) estimate the prevalence of beneficiaries with diabetes aged between 40 and 75 years; (b) estimate the prevalence of statin utilization among beneficiaries with diabetes; and (c) estimate secondary adherence to statins among beneficiaries with diabetes. METHODS: With pharmacy claims data from a commercial pharmacy benefit manager (PBM) in the Commonwealth of Puerto Rico, this study used a retrospective longitudinal design to analyze all pharmacy claims generated by 115,674 beneficiaries aged between 40 and 75 years with continuous enrollment during 2018. Beneficiaries with diabetes were defined by having ≥ 2 pharmacy claims for antidiabetic agents during 2018. Statin utilization was defined by having ≥ 1 pharmacy claim for statins among beneficiaries with diabetes. The proportion of days covered (PDC) was used to measure secondary adherence to statins. Parametric and nonparametric statistics were used to describe statin utilization and adherence. RESULTS: The prevalence of beneficiaries with diabetes was 7.8%. Of the 8,975 beneficiaries with diabetes, 5,129 (57.1%) received ≥ 1 prescription for a statin. Older males with diabetes were more likely to receive prescriptions for statins. The median PDC for the 4,553 beneficiaries with ≥ 2 prescriptions for statins was 63.4%; 3,306 (72.6%) beneficiaries filled their statin prescriptions for a 30-day supply only; and 1,252 (27.5%) beneficiaries had a PDC ≥ 80%. The highest PDC (92.3%) was observed for beneficiaries who received statins for a 90-day supply only. CONCLUSIONS: This is the first study that has measured statin utilization and adherence among patients with diabetes living in Puerto Rico. The utilization and adherence to statins among privately insured beneficiaries with diabetes in Puerto Rico are suboptimal. Future studies should focus on understanding the reasons for the suboptimal use of statins and on potential interventions at the beneficiary and provider level to increase statin utilization. DISCLOSURES: No outside funding supported this study. The authors have no conflicts of interest or financial disclosures to disclose related to this study.

Prevalence of Rheumatoid Arthritis and Drug Dispensing Patterns Among Medicaid and Medicaid-Medicare Dually Eligible Beneficiaries in Puerto Rico.

OBJECTIVE: To estimate the prevalence of rheumatoid arthritis (RA) in Puerto Rico, to describe disease-modifying antirheumatic drug (DMARD) dispensing patterns by prescriber specialty, and to illustrate the impact of RA case definition on the estimated prevalence. METHODS: This study estimated the prevalence of RA in Puerto Rico during 2016 among Medicaid and Medicaid-Medicare dually eligible beneficiaries of the Mi Salud health care plan, a federally funded health insurance program. DMARD dispensing and cost patterns were described and stratified by provider specialty. A sensitivity analysis was conducted to evaluate the effect of RA case definition on estimated prevalence. RESULTS: The prevalence of RA in 2016 was estimated to be 2 cases per 1,000 beneficiaries, with 3 per 1,000 beneficiaries among females, 4.5 times that of males. In total, 44% of beneficiaries received conventional synthetic DMARDs (csDMARDs) only, 32% received biologic or targeted synthetic DMARDs (b/tsDMARDs) only, and 24% received a combination of csDMARDs and b/tsDMARDs. Rheumatologists and a combination of specialties accounted for the highest median number of dispensed DMARDs, with 14 each. A sensitivity analysis revealed that when RA cases with ≥3 medical claims were restricted to having ≥1 DMARD claim, the estimated prevalence changed from 6 to 3 cases per 1,000 beneficiaries. CONCLUSION: The prevalence of RA in Puerto Rico in this study is lower than reported in the mainland US, possibly due to more stringent criteria to define RA. DMARD dispensing and cost patterns are similar to those found in other studies. Claims algorithms that identify RA have higher validity when pharmacy data is included.